Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet (SIAM J. Sci. Comput., 2016)

A Universal Marginalizer for Amortized Inference in Generative Models. - Laura Douglas; Iliyan Zarov; Konstantinos Gourgoulias; Chris Lucas 002; Chris Hart; Adam Baker; Maneesh Sahani; Yura Perov; Saurabh Johri (CoRR, 2017)

Information criteria for quantifying loss of reversibility in parallelized KMC. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet (J. Comput. Phys., 2017)

Universal Marginalizer for Amortised Inference and Embedding of Generative Models. - Robert Walecki; Albert Buchard; Kostis Gourgoulias; Chris Hart; Maria Lomeli; Alexandre K. W. Navarro; Max Zwiessele; Yura Perov; Saurabh Johri (CoRR, 2018)

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. - Yura Perov; Logan Graham; Kostis Gourgoulias; Jonathan G. Richens; Ciarán M. Lee; Adam Baker; Saurabh Johri (AABI, 2019)

Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs. - Robert Walecki; Kostis Gourgoulias; Adam Baker; Chris Hart; Chris Lucas 002; Max Zwiessele; Albert Buchard; Maria Lomeli; Yura Perov; Saurabh Johri (CoRR, 2019)

Masking schemes for universal marginalisers. - Divya Gautam; Maria Lomeli; Kostis Gourgoulias; Daniel H. Thompson; Saurabh Johri (CoRR, 2020)

Learning medical triage from clinicians using Deep Q-Learning. - Albert Buchard; Baptiste Bouvier; Giulia Prando; Rory Beard; Michail Livieratos; Dan Busbridge; Daniel H. Thompson; Jonathan G. Richens; Yuanzhao Zhang; Adam Baker; Yura Perov; Kostis Gourgoulias; et al. (CoRR, 2020)

How Biased Is Your Model? Concentration Inequalities, Information and Model Bias. - Konstantinos Gourgoulias; Markos A. Katsoulakis; Luc Rey-Bellet; Jie Wang 030 (IEEE Trans. Inf. Theory, 2020)

An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning. - Najah Ghalyan; Kostis Gourgoulias; Yash Satsangi; Sean J. Moran; Maxime Labonne; Joseph Sabelja (CoRR, 2023)

DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights using the Fisher Diagonal. - Jiaeli Shi; Najah Ghalyan; Kostis Gourgoulias; John F. Buford; Sean J. Moran (CoRR, 2023)

DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights Using the Fisher Diagonal. - Jialei Shi; Kostis Gourgoulias; John F. Buford; Sean J. Moran; Najah Ghalyan (ECCV Workshops (18), 2024)

Estimating class separability of text embeddings with persistent homology. - Kostis Gourgoulias; Najah Ghalyan; Maxime Labonne; Yash Satsangi; Sean J. Moran; Joseph Sabelja (Trans. Mach. Learn. Res., 2024)

Efficient and Explainable Anomaly Detection in Financial System Logs Using Statistical Modeling. - Mohammed Ayub; Mauro Annarumma; Gaston Liberman; David Algorry; Kostis Gourgoulias; Najah Ghalyan; Sean J. Moran (FinanSE@ICSE, 2025)

ADkit: A Framework for Anomaly Detection from Natural Language. - Kostis Gourgoulias; Senad Ibraimoski; Alexandru-Petre Cazan; Mohammed Ayub; Andre Frade; Leandro Martin Rios; Sean J. Moran (FinanSE@ICSE, 2025)

Using AI/ML to Find and Remediate Enterprise Secrets in Code and Document Sharing Platforms. - Gregor Kerr; David Algorry; Senad Ibraimoski; Peter Maciver; Kostis Gourgoulias; Sean J. Moran (FinanSE@ICSE, 2025)